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<!doctype html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>Granite Docling Image Converter</title>
    <script src="https://cdn.tailwindcss.com"></script>
    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet" />
    <style>
      body {
        font-family: "Inter", sans-serif;
      }
      .loader {
        border-top-color: #3498db;
        animation: spin 1s linear infinite;
      }
      .loader-large {
        border: 8px solid #e5e7eb;
        border-top: 8px solid #3498db;
        animation: spin 1s linear infinite;
      }
      .loader-small {
        border: 4px solid #e5e7eb;
        border-top: 4px solid #3498db;
        animation: spin 1s linear infinite;
      }
      @keyframes spin {
        0% {
          transform: rotate(0deg);
        }
        100% {
          transform: rotate(360deg);
        }
      }
      /* Custom toggle switch */
      .toggle-checkbox:checked {
        right: 0;
        border-color: #4f46e5;
      }
      .toggle-checkbox:checked + .toggle-label {
        background-color: #4f46e5;
      }
      .overlay {
        border: 2px solid var(--overlay-color);
        transition: background-color 0.2s;
      }
      .overlay:hover {
        background-color: rgba(var(--overlay-color-rgb), 0.7);
      }
    </style>
  </head>
  <body class="bg-gray-100 text-gray-800 antialiased">
    <div id="model-loader-overlay" class="fixed inset-0 bg-black bg-opacity-60 flex flex-col items-center justify-center z-50">
      <div class="loader-large ease-linear rounded-full h-24 w-24 mb-4"></div>
      <h2 class="text-center text-white text-xl font-semibold">Loading Model...</h2>
      <p class="text-center text-white text-md mt-2">This may take a moment. The model is being downloaded to your browser.</p>
      <progress id="model-progress" value="0" max="100" class="w-64 mt-4 bg-gray-200 rounded-full h-2"></progress>
      <p id="progress-text" class="text-center text-white text-sm mt-2">0%</p>
    </div>

    <main class="container mx-auto p-4 md:p-8">
      <header class="text-center mb-8">
        <h1 class="text-4xl font-bold text-gray-900">Granite Docling WebGPU</h1>
        <p class="text-lg text-gray-600 mt-2">Convert document images to HTML using 🤗 Transformers.js!</p>
      </header>

      <div class="grid grid-cols-1 lg:grid-cols-2 gap-8">
        <!-- Left Panel: Image Input -->
        <div class="bg-white p-6 rounded-lg shadow-md">
          <h2 class="text-2xl font-semibold mb-4">1. Select an Image</h2>

          <div
            id="image-drop-area"
            class="border-2 border-dashed border-gray-300 rounded-lg p-8 text-center cursor-pointer transition-colors duration-200 hover:border-indigo-500 hover:bg-indigo-50"
          >
            <div id="image-placeholder">
              <svg class="mx-auto h-12 w-12 text-gray-400" stroke="currentColor" fill="none" viewBox="0 0 48 48" aria-hidden="true">
                <path
                  d="M28 8H12a4 4 0 00-4 4v20m32-12v8m0 0v8a4 4 0 01-4 4H12a4 4 0 01-4-4v-4m32-4l-3.172-3.172a4 4 0 00-5.656 0L28 28M8 32l9.172-9.172a4 4 0 015.656 0L28 28m0 0l4 4m4-24h8m-4-4v8"
                  stroke-width="2"
                  stroke-linecap="round"
                  stroke-linejoin="round"
                />
              </svg>
              <p class="mt-2 text-sm text-gray-600">
                <span class="font-semibold text-indigo-600">Drag and drop</span>
                or click to select a file
              </p>
              <p class="text-xs text-gray-500">PNG, JPG, WEBP</p>
              <input type="file" id="file-input" class="hidden" accept="image/*" />
            </div>
            <div id="image-preview-container" class="hidden relative">
              <img id="image-preview" src="" alt="Selected image" class="mx-auto rounded-md shadow-sm" />
              <button
                id="remove-image-btn"
                class="absolute top-2 right-2 z-10 bg-red-500 text-white rounded-full p-2 hover:bg-red-600 transition-colors focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-red-500"
              >
                <svg xmlns="http://www.w3.org/2000/svg" class="h-5 w-5" viewBox="0 0 20 20" fill="currentColor">
                  <path
                    fill-rule="evenodd"
                    d="M4.293 4.293a1 1 0 011.414 0L10 8.586l4.293-4.293a1 1 0 111.414 1.414L11.414 10l4.293 4.293a1 1 0 01-1.414 1.414L10 11.414l-4.293 4.293a1 1 0 01-1.414-1.414L8.586 10 4.293 5.707a1 1 0 010-1.414z"
                    clip-rule="evenodd"
                  />
                </svg>
              </button>
            </div>
          </div>

          <div class="mt-4 flex">
            <input
              type="text"
              id="prompt-input"
              class="flex-1 px-3 py-2 border border-gray-300 rounded-md shadow-sm focus:outline-none focus:ring-indigo-500 focus:border-indigo-500 sm:text-sm"
              value="Convert this page to docling."
            />
            <button
              id="generate-btn"
              class="ml-2 px-4 py-2 bg-indigo-600 text-white rounded-md hover:bg-indigo-700 disabled:bg-gray-400 disabled:cursor-not-allowed"
            >
              Generate
            </button>
          </div>

          <h3 class="text-lg font-semibold mt-6 mb-3" id="examples-title">Or try an example:</h3>
          <div class="flex space-x-4 overflow-x-auto" id="examples-container">
            <img
              src="./assets/document.png"
              class="example-image h-36 w-auto border-2 border-gray-200 rounded-md cursor-pointer hover:border-indigo-500 transition-colors"
              alt="Example document"
              data-prompt="Convert this page to docling."
              title="Document parsing"
            />
            <img
              src="./assets/chart.png"
              class="example-image h-36 w-auto border-2 border-gray-200 rounded-md cursor-pointer hover:border-indigo-500 transition-colors"
              alt="Example chart"
              data-prompt="Convert chart to OTSL."
              title="Chart parsing"
            />
            <img
              src="./assets/table.jpg"
              class="example-image h-36 w-auto border-2 border-gray-200 rounded-md cursor-pointer hover:border-indigo-500 transition-colors"
              alt="Example table"
              data-prompt="Convert this table to OTSL."
              title="Table parsing"
            />
            <img
              src="./assets/code.jpg"
              class="example-image h-36 w-auto border-2 border-gray-200 rounded-md cursor-pointer hover:border-indigo-500 transition-colors"
              alt="Example code"
              data-prompt="Convert code to text."
              title="Code parsing"
            />
          </div>
        </div>

        <!-- Right Panel: Output -->
        <div class="bg-white p-6 rounded-lg shadow-md flex flex-col">
          <div class="flex justify-between items-center mb-4">
            <h2 class="text-2xl font-semibold">2. View Result</h2>
            <div id="processing-indicator" class="flex items-center space-x-2 text-gray-500 hidden">
              <div class="loader-small ease-linear rounded-full h-6 w-6"></div>
              <p class="text-sm">Processing image...</p>
            </div>
            <div class="flex items-center space-x-2">
              <span class="text-sm font-medium">Docling</span>
              <div class="relative inline-block w-10 mr-2 align-middle select-none transition duration-200 ease-in">
                <input
                  type="checkbox"
                  name="toggle"
                  id="view-toggle"
                  class="toggle-checkbox absolute block w-6 h-6 rounded-full bg-white border-4 appearance-none cursor-pointer"
                  checked
                />
                <label for="view-toggle" class="toggle-label block overflow-hidden h-6 rounded-full bg-gray-300 cursor-pointer"></label>
              </div>
              <span class="text-sm font-medium text-indigo-600">HTML</span>
            </div>
          </div>

          <div id="output-container" class="flex-1 border border-gray-200 rounded-lg overflow-hidden bg-gray-50">
            <div id="welcome-message" class="h-full flex items-center justify-center text-center text-gray-500">
              <p>Select an image to see the result here.</p>
            </div>

            <!-- Docling Output -->
            <div id="docling-view" class="h-full p-4 hidden">
              <pre class="h-full whitespace-pre-wrap text-sm overflow-auto"><code id="docling-output"></code></pre>
            </div>

            <!-- HTML Output -->
            <div id="html-view" class="h-full w-full">
              <iframe id="html-iframe" sandbox="allow-scripts" class="w-full h-full border-0"></iframe>
            </div>
          </div>
        </div>
      </div>
    </main>

    <!-- Hidden canvas for image processing -->
    <canvas id="hidden-canvas" class="hidden"></canvas>

    <script type="module">
      import { AutoProcessor, AutoModelForVision2Seq, RawImage, TextStreamer, load_image } from "https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.7.5";
      import { doclingToHtml } from "./parser.js";

      const modelLoaderOverlay = document.getElementById("model-loader-overlay");
      const imageDropArea = document.getElementById("image-drop-area");
      const imagePlaceholder = document.getElementById("image-placeholder");
      const imagePreviewContainer = document.getElementById("image-preview-container");
      const imagePreview = document.getElementById("image-preview");
      const removeImageBtn = document.getElementById("remove-image-btn");
      const fileInput = document.getElementById("file-input");
      const exampleImages = document.querySelectorAll(".example-image");
      const examplesContainer = document.getElementById("examples-container");
      const examplesTitle = document.getElementById("examples-title");

      const processingIndicator = document.getElementById("processing-indicator");
      const welcomeMessage = document.getElementById("welcome-message");
      const doclingView = document.getElementById("docling-view");
      const htmlView = document.getElementById("html-view");
      const doclingOutput = document.getElementById("docling-output");
      const htmlIframe = document.getElementById("html-iframe");
      const viewToggle = document.getElementById("view-toggle");
      const hiddenCanvas = document.getElementById("hidden-canvas");
      const promptInput = document.getElementById("prompt-input");
      const generateBtn = document.getElementById("generate-btn");

      let model, processor;
      let currentImageWidth, currentImageHeight;
      let currentImage = null;

      /**
       * Loads and initializes the model and processor.
       */
      async function initializeModel() {
        try {
          const model_id = "onnx-community/granite-docling-258M-ONNX";
          processor = await AutoProcessor.from_pretrained(model_id);

          const progress = {};
          model = await AutoModelForVision2Seq.from_pretrained(model_id, {
            dtype: {
              embed_tokens: "fp16", // fp32 (231 MB) | fp16 (116 MB)
              vision_encoder: "fp32", // fp32 (374 MB)
              decoder_model_merged: "fp32", // fp32 (658 MB) | q4 (105 MB), q4 sometimes into repetition issues
            },
            device: "webgpu",
            progress_callback: (data) => {
              if (data.status === "progress" && data.file?.endsWith?.("onnx_data")) {
                progress[data.file] = data;
                const progressPercent = Math.round(data.progress);

                if (Object.keys(progress).length !== 3) return;
                let sum = 0;
                let total = 0;
                for (const [key, val] of Object.entries(progress)) {
                  sum += val.loaded;
                  total += val.total;
                }

                const overallPercent = Math.round((sum / total) * 100);
                document.getElementById("model-progress").value = overallPercent;
                document.getElementById("progress-text").textContent = overallPercent + "%";
              }
            },
          });
          modelLoaderOverlay.style.display = "none";
          console.log("Model loaded successfully.");
        } catch (error) {
          console.error("Failed to load model:", error);
          modelLoaderOverlay.innerHTML = `
                    <h2 class="text-center text-red-500 text-xl font-semibold">Failed to Load Model</h2>
                    <p class="text-center text-white text-md mt-2">Please refresh the page to try again. Check the console for errors.</p>
                `;
        }
      }

      /**
       * Processes an image and generates Docling text.
       * @param {ImageBitmap|HTMLImageElement} imageObject An image object to process.
       */
      async function processImage(imageObject) {
        if (!model || !processor) {
          alert("Model is not loaded yet. Please wait.");
          return;
        }

        // Reset UI
        setUiState("processing");
        clearOverlays();
        let fullText = "";
        doclingOutput.textContent = "";
        htmlIframe.srcdoc = "";

        try {
          // 1. Draw image to canvas and get RawImage
          const ctx = hiddenCanvas.getContext("2d");
          hiddenCanvas.width = imageObject.width;
          hiddenCanvas.height = imageObject.height;
          ctx.drawImage(imageObject, 0, 0);
          const image = RawImage.fromCanvas(hiddenCanvas);

          // 2. Create input messages
          const messages = [
            {
              role: "user",
              content: [{ type: "image" }, { type: "text", text: promptInput.value }],
            },
          ];

          // 3. Prepare inputs for the model
          const text = processor.apply_chat_template(messages, {
            add_generation_prompt: true,
          });
          const inputs = await processor(text, [image], {
            do_image_splitting: true,
          });
          // 5. Generate output
          await model.generate({
            ...inputs,
            max_new_tokens: 4096,
            streamer: new TextStreamer(processor.tokenizer, {
              skip_prompt: true,
              skip_special_tokens: false,
              callback_function: (streamedText) => {
                fullText += streamedText;
                doclingOutput.textContent += streamedText;
              },
            }),
          });

          // Strip <|end_of_text|> from the end
          fullText = fullText.replace(/<\|end_of_text\|>$/, "");
          doclingOutput.textContent = fullText;

          // Parse loc tags and create overlays
          const tagRegex = /<(\w+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/g;
          const overlays = [];
          let match;
          while ((match = tagRegex.exec(fullText)) !== null) {
            const tagType = match[1];
            const locs = [parseInt(match[2]), parseInt(match[3]), parseInt(match[4]), parseInt(match[5])];
            overlays.push({ tagType, locs });
          }
          const colorMap = {};
          function getRandomColor() {
            return `rgb(${Math.floor(Math.random() * 256)}, ${Math.floor(Math.random() * 256)}, ${Math.floor(Math.random() * 256)})`;
          }
          const imgRect = imagePreview.getBoundingClientRect();
          const containerRect = imagePreviewContainer.getBoundingClientRect();
          const imageOffsetLeft = imgRect.left - containerRect.left;
          const imageOffsetTop = imgRect.top - containerRect.top;
          const scaleX = imgRect.width / currentImageWidth;
          const scaleY = imgRect.height / currentImageHeight;
          overlays.forEach(({ tagType, locs }) => {
            const color = colorMap[tagType] || (colorMap[tagType] = getRandomColor());
            const [leftLoc, topLoc, rightLoc, bottomLoc] = locs;
            const left = imageOffsetLeft + (leftLoc / 500) * currentImageWidth * scaleX;
            const top = imageOffsetTop + (topLoc / 500) * currentImageHeight * scaleY;
            const width = ((rightLoc - leftLoc) / 500) * currentImageWidth * scaleX;
            const height = ((bottomLoc - topLoc) / 500) * currentImageHeight * scaleY;
            const overlay = document.createElement("div");
            overlay.className = "overlay";
            overlay.style.setProperty('--overlay-color', color);
            const rgbMatch = color.match(/rgb\((\d+),\s*(\d+),\s*(\d+)\)/);
            overlay.style.setProperty('--overlay-color-rgb', `${rgbMatch[1]},${rgbMatch[2]},${rgbMatch[3]}`);
            overlay.style.position = "absolute";
            overlay.style.left = left + "px";
            overlay.style.top = top + "px";
            overlay.style.width = width + "px";
            overlay.style.height = height + "px";
            imagePreviewContainer.appendChild(overlay);
          });

          // After generation, create the HTML iframe
          htmlIframe.srcdoc = doclingToHtml(fullText);
        } catch (error) {
          console.error("Error during image processing:", error);
          doclingOutput.textContent = `An error occurred: ${error.message}`;
        } finally {
          setUiState("result");
        }
      }

      /**
       * Handles the selection of an image file.
       * @param {File|string} source The image file or URL.
       */
      function handleImageSelection(source) {
        const reader = new FileReader();
        const img = new Image();

        img.onload = () => {
          currentImageWidth = img.naturalWidth;
          currentImageHeight = img.naturalHeight;
          currentImage = img;
          imagePreview.src = img.src;
          imagePlaceholder.classList.add("hidden");
          imagePreviewContainer.classList.remove("hidden");
          examplesContainer.classList.add("hidden");
          examplesTitle.classList.add("hidden");
          processImage(img);
        };

        img.onerror = () => {
          alert("Failed to load image.");
        };

        if (typeof source === "string") {
          // It's a URL
          // To avoid CORS issues with canvas, we can try to fetch it first
          fetch(source)
            .then((res) => res.blob())
            .then((blob) => {
              img.src = URL.createObjectURL(blob);
            })
            .catch((e) => {
              console.error("CORS issue likely. Trying proxy or direct load.", e);
              // Fallback to direct load which might taint the canvas
              img.crossOrigin = "anonymous";
              img.src = source;
            });
        } else {
          // It's a File object
          reader.onload = (e) => {
            img.src = e.target.result;
          };
          reader.readAsDataURL(source);
        }
      }

      /**
       * Manages the visibility of UI components based on the app state.
       * @param {'initial'|'processing'|'result'} state The current state.
       */
      function setUiState(state) {
        welcomeMessage.style.display = "none";
        processingIndicator.classList.add("hidden");
        doclingView.classList.add("hidden");
        htmlView.classList.add("hidden");

        if (state === "initial") {
          welcomeMessage.style.display = "flex";
          generateBtn.disabled = true;
        } else if (state === "processing") {
          viewToggle.checked = false;
          processingIndicator.classList.remove("hidden");
          doclingView.classList.remove("hidden");
          generateBtn.disabled = true;
        } else if (state === "result") {
          viewToggle.checked = true;
          htmlView.classList.remove("hidden");
          generateBtn.disabled = false;
        }
      }

      /**
       * Clears all overlay divs from the image preview container.
       */
      function clearOverlays() {
        document.querySelectorAll(".overlay").forEach((el) => el.remove());
      }

      // Drag and Drop
      imageDropArea.addEventListener("click", () => fileInput.click());
      imageDropArea.addEventListener("dragover", (e) => {
        e.preventDefault();
        imageDropArea.classList.add("border-indigo-500", "bg-indigo-50");
      });
      imageDropArea.addEventListener("dragleave", () => {
        imageDropArea.classList.remove("border-indigo-500", "bg-indigo-50");
      });
      imageDropArea.addEventListener("drop", (e) => {
        e.preventDefault();
        imageDropArea.classList.remove("border-indigo-500", "bg-indigo-50");
        const files = e.dataTransfer.files;
        if (files.length > 0 && files[0].type.startsWith("image/")) {
          handleImageSelection(files[0]);
        }
      });

      // File input
      fileInput.addEventListener("change", (e) => {
        const files = e.target.files;
        if (files.length > 0) {
          handleImageSelection(files[0]);
        }
      });

      // Example images
      exampleImages.forEach((img) => {
        img.addEventListener("click", () => {
          promptInput.value = img.dataset.prompt;
          handleImageSelection(img.src);
        });
      });

      // Remove image
      removeImageBtn.addEventListener("click", (e) => {
        e.stopPropagation();
        currentImage = null;
        imagePreview.src = "";
        fileInput.value = ""; // Reset file input
        imagePlaceholder.classList.remove("hidden");
        imagePreviewContainer.classList.add("hidden");
        examplesContainer.classList.remove("hidden");
        examplesTitle.classList.remove("hidden");
        setUiState("initial");
        doclingOutput.textContent = "";
        htmlIframe.srcdoc = "";
        clearOverlays();
      });

      // View toggle
      viewToggle.addEventListener("change", () => {
        const isHtmlView = viewToggle.checked;
        htmlView.classList.toggle("hidden", !isHtmlView);
        doclingView.classList.toggle("hidden", isHtmlView);
      });

      // Generate button
      generateBtn.addEventListener("click", () => {
        if (currentImage) {
          processImage(currentImage);
        }
      });

      document.addEventListener("DOMContentLoaded", () => {
        setUiState("initial"); // Set initial view correctly
        initializeModel();
      });
    </script>
  </body>
</html>